Name
Abstract | ||
|---|---|---|
In this paper, an emerging artificial neural network (ECANN) is proposed. Abstracting from a latest research in neuroscience, electromagnetic coupling among neuron activities is introduced into the model. Besides, the overall network can be viewed as a system with physical significance of circuitry, and each neuron is presented as differential equation. At the mean time, the spatial grid topology is employed in order to develop its parallelism. This artificial neural network is designed for fitting and predicting dynamic data, and has successfully worked in simulation part of this paper. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-38786-9_7 | BICS |
Keywords | Field | DocType |
overall network,differential equation,physical significance,simulation part,neuron activity,latest research,dynamic data,spatial topology,electromagnetic coupling,mean time,artificial neural network | Topology,Nervous system network models,Differential equation,Physical neural network,Computer science,Network simulation,Time delay neural network,Dynamic data,Artificial intelligence,Artificial neural network,Grid | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ziyin Wang | 1 | 7 | 3.96 |
| Mandan Liu | 2 | 4 | 3.44 |
| Xiang Ren | 3 | 885 | 60.08 |
| Yi-Cheng Cheng | 4 | 54 | 7.15 |